Vehicle lane tracking systems may employ visual object recognition to identify bounding lane lines marked on a road. Through these systems, visual processing techniques may estimate a position between the vehicle and the respective lane lines, as well as a heading of the vehicle relative to the lane. Such processing/recognition techniques, however, may be processor intensive and/or may require heavy filtering. This may result in the position estimates being time-delayed relative to the acquisition of the video information. Additionally, visual information may be acquired sporadically due to visual obstructions, ambient visibility limitations, dirt/debris that may cloud the visibility of the camera lens, and/or the need to aggregate multiple sequential frames for certain video filtering methods. Such latency and/or sporadic or slow refresh rates may lead to system instabilities or may compromise the vehicle's response time/accuracy if an automatic path correction is warranted.